nsarfima: Methods for Fitting and Simulating Non-Stationary ARFIMA Models

Routines for fitting and simulating data under autoregressive fractionally integrated moving average (ARFIMA) models, without the constraint of covariance stationarity. Two fitting methods are implemented, a pseudo-maximum likelihood method and a minimum distance estimator. Mayoral, L. (2007) <doi:10.1111/j.1368-423X.2007.00202.x>. Beran, J. (1995) <doi:10.1111/j.2517-6161.1995.tb02054.x>.

Version:	0.2.0.0
Depends:	R (≥ 3.6.0)
Published:	2020-08-06
Author:	Benjamin Groebe [aut, cre]
Maintainer:	Benjamin Groebe <ben.groebe at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	no
In views:	TimeSeries
CRAN checks:	nsarfima results

Documentation:

Reference manual:

nsarfima.pdf

Downloads:

Package source:	nsarfima_0.2.0.0.tar.gz
Windows binaries:	r-prerel: nsarfima_0.2.0.0.zip, r-release: nsarfima_0.2.0.0.zip, r-oldrel: nsarfima_0.2.0.0.zip
macOS binaries:	r-prerel (arm64): nsarfima_0.2.0.0.tgz, r-release (arm64): nsarfima_0.2.0.0.tgz, r-oldrel (arm64): nsarfima_0.2.0.0.tgz, r-prerel (x86_64): nsarfima_0.2.0.0.tgz, r-release (x86_64): nsarfima_0.2.0.0.tgz
Old sources:	nsarfima archive

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